Data Engineer (Microsoft Fabric & Azure)

About the role

Entalpi, a technology consulting and engineering company covering cloud and infrastructure, data analytics, data governance, DevOps and digital transformation, is looking for a mid-level Data Engineer to join its Data & Analytics engineering team. You will contribute to the design, development and optimization of modern data platforms, focusing on Microsoft Fabric, Azure data services and enterprise data engineering solutions.

Key responsibilities

• Design, develop and maintain scalable data pipelines and ETL/ELT processes
• Build and optimize data warehouses, data lakes and lakehouse architectures with Microsoft Fabric and Azure
• Develop data integration workflows with Azure Data Factory, Fabric Data Factory and related tools
• Implement ingestion, transformation, orchestration and processing across multiple data sources
• Use SQL, Python, PySpark and Apache Spark; work with Fabric components such as OneLake, Lakehouse, Warehouse, Dataflows Gen2 and Notebooks
• Design dimensional data models (star schemas, fact and dimension tables) and batch and incremental processing, including CDC
• Add data quality checks, validation, monitoring and error handling; optimize SQL, Spark workloads and storage for performance and cost
• Support migrations from traditional warehouses to cloud-native architectures, and implement version control, automated deployment and CI/CD
• Collaborate with data architects, BI developers, DevOps engineers and business stakeholders, and prepare technical documentation

Required profile

• Minimum 3 years of professional experience in data engineering, data platform engineering, BI engineering or related roles
• Strong hands-on experience with Azure data services and cloud-based data engineering
• Solid understanding of data modeling, dimensional modeling and modern architectures (data warehouse, data lake, lakehouse, medallion)
• Good command of written and spoken English

Required skills

• Advanced SQL and T-SQL, including query optimization
• Python and PySpark/Apache Spark
• Azure Data Factory, Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure SQL Database, Azure Databricks
• Microsoft Fabric or strong familiarity with its architecture
• Nice to have: Snowflake, AWS data services, Airflow, Kafka, dbt, Trino, PostgreSQL, Power BI, Delta Lake, Terraform, Docker, Kubernetes, FinOps, Microsoft Purview